For years, automation has been seen as the cure to all enterprise IT inefficiencies, promising to reduce costs, boost productivity and accelerate resolution times. Yet automation has become a reactive response to IT overload, papering over the cracks that IT support is scrambling to fix, rather than truly solving them.
Current automation efforts leave the true blockers of productivity untouched. Even as automation provides quick, autonomous fixes, employees are still being dragged down by IT failures, inefficient workflows and tool overload.
To unlock tangible efficiency gains, CIOs need to rethink their approach to how automation can better help IT support teams. Automation must become part of a wider strategy that tackles the root causes of inefficiency. Only then can organizations address the barriers that are holding their teams back.
What support requests don’t tell you
Despite significant investment in automation for IT support, many organizations aren’t seeing meaningful returns. For instance, only 25% of businesses have seen ROI from AI. And there’s a clear reason why: organizations are automating the wrong things. They focus on surface-level symptoms and resulting workload rather than addressing the underlying causes of IT issues.
Take something as simple as password resets. Automated processes can be put in place to ensure that employees get the help they need. But login issues may only be part of the problem with any given application. They may also be plagued by performance problems or regular crashes.
So, while the login issue may be resolved, the other problems remain, and so does the employee’s frustration.
At the heart of this challenge is the data driving automation decisions. Most organizations rely on metrics like ticket volumes or support requests to determine where to focus automation efforts. But this data only scratches the surface of the employee experience and doesn’t provide a full view of the problems facing teams on a daily basis.
And to reiterate, it focusses on fixing the workload problem and not the root cause. And does nothing to bring relief to the employee other than a fast fox.
Automation’s blind spot
This surface-level view means organizations are failing to get the full value from automation deployments. And the consequences have a far reach.
Teams rely more than ever on using online applications and devices for their work. Research shows that up to 90% of staff spend as much as five hours a day using work messaging apps like Slack or Microsoft Teams. But if these applications don’t work as they should, teams are forced to spend time waiting for IT support to resolve IT issues.
It may seem small, but the time wasted addressing IT issues chips away at employee efficiency each day. Across an entire workforce, these delays multiply over time, taking a significant toll
on productivity. But it’s the organization that pays the price. When employees can’t operate at their best, business performance and revenue will inevitably drop.
The core reason why automation efforts fall short is a lack of insight into the issues that are causing employees’ frustrations. After all, if a business doesn’t know what’s truly impacting their employees, how are they supposed to fix it?
To move beyond the break-fix cycle, organizations need full visibility into the end-user experience. Only then can automation address issues before productivity takes a hit. So how can CIOs get their automation efforts back on track?
From reactive to real-time
To break free from ticket-driven automation, organizations need to move away from using standalone systems and surface metrics. Instead, they need access to historical and real-time data that captures technical performance and employee sentiment.
Automation is only as effective as the data it is fed. To tackle IT friction, this data must reflect employee pain points resulting from their devices, such as application crashes, login failures or poor network performance.
This is where data on the Digital Employee Experience (DEX) comes into play. Using DEX data, automation can act on the problems before they escalate or spread.
For instance, rather than waiting for employees to submit tickets about an application crashing, DEX-powered automation can act early, reverting a faulty update or installing the latest patch before the employee even notices and before it impacts others.
As a result, employees remain connected to digital tools like Microsoft Teams and Slack that they rely on to do their work. And as less time is spent waiting on IT support teams to diagnose and fix IT issues, teams can spend more time doing the real work and contributing to the business.
Smarter automation starts here
Automation can no longer be about fixing surface-level symptoms as they appear. To stop playing catch-up, automation must address the deeper productivity problems that slow teams down, rather than just looking for ways to automate out of a workload problem.
The shift from reactive to proactive and finally to preventative starts with the data being fed into the automation. By using DEX insights, organizations gain the visibility needed to anticipate and resolve pain points before they impact employees. Automation should not be about patching over issues but preventing them altogether.
The difference is clear: when grounded in DEX data, automation will become proactive and intelligent, unlocking stronger ROI for the business and sustained productivity improvements across the board.
